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CRM Myth Busters: Breaking Down the Common Misconceptions

Here are the top mistakes that undermine CRM strategies and how to fix them

Adapted with permission from 1to1 Media.

Today, most business leaders recognize that customer relationship management (CRM) is important for the success of their business. Companies continue to invest heavily in technology solutions, including CRM platforms, to better understand and engage more effectively with customers. In fact, the worldwide CRM software market grew to $23.2 billion in 2014, up 13.3 percent from $20.4 billion in 2013, according to Gartner.

However, misconceptions about how to implement and leverage CRM can prevent companies from reaping the full benefits of their investments. Inaccurate data, fragmented technology implementations, data silos, and other challenges can cause CRM efforts to stumble. Analysts and industry experts challenge the top CRM myths that businesses need to be aware of as well as technology trends that are driving the development of the CRM space.

All Data Must Be ‘Cleaned’

Companies understand that accurate data is the foundation of a successful CRM strategy, but setting out to scrub your databases of inaccuracies without clear goals is an inefficient use of time and resources, say analysts. “The problem is that data quality initiatives are difficult to undertake if they are not tied to a real CRM project with quantifiable benefits,” notes Kate Leggett, vice president and principal analyst at Forrester Research. “Best practices start with building a business case which focuses on the impact poor quality data has on critical business and customer-facing processes as opposed to just focusing on the data itself.”

For instance, marketers could spend time removing duplicate names from a customer database. However, those efforts will be wasted if the contacts are outdated or are irrelevant to the campaign. Instead, Leggett recommends that CRM and data management experts define the following criteria: the business processes, decisions, and customer interactions that are most important to their organization; the data used to support those processes; the systems and processes used to capture and update customer data; and the level of confidence when using this data.

The More Data the Better

In their rush to understand customer expectations and preferences, companies have captured and stored huge volumes of data that goes unused. “You can have too much of a good thing,” says Robert Wollan, global managing director of sales and customer services at Accenture Strategy. “We recommend a ‘data weight loss’ program that turns the telescope around – starting with the experiences and operations that will drive the most business value and reverse engineer what data the company needs to drive the results. The rest becomes candidates for complexity reduction.”

CRM Data Only Belongs to Certain Departments

Companies that treat CRM data as something owned and used only by specific departments are creating data silos that will make it difficult to gain a full understanding of the customer, notes Rebecca Wettemann, vice president of research at Nucleus Research.

“From a data perspective, one of the biggest challenges companies create for themselves is in creating separate data for sales, marketing, and customer service, usually because at least initially different apps and processes are used for each area,” Wettemann says. “Down the road, this creates integration and data latency problems and makes it more difficult for companies to truly view a complete record of customer interactions and history.”

"Breaking down barriers between data is a major challenge for most companies"

Sean Carithers, vice president of enterprise solutions at TeleTech

"Breaking down barriers between data is a major challenge for most companies"

Sean Carithers, vice president of enterprise solutions at TeleTech

Sean Carithers, vice president of enterprise solutions at TeleTech, agrees that “breaking down barriers between data is a major challenge for most companies.” To avoid this problem, companies should have a strategy for integrating their various datasets. Data experts, Carithers continues, should ask themselves “how does our CRM data fit into our overall customer data strategy and where do we want to house that data?” Deciding early on what the organization’s customer engagement goals are and developing a strategy for integrating the necessary datasets to accomplish those goals will help to streamline these efforts, Carithers notes.

Businesses are Stuck with Legacy Systems

Executives tend to assume that making huge investments in populating data and customizations into a single system means “they should stick with it until it literally falls apart,” Wettemann observes. However, advances in usability and analytics capabilities over the past few years have made it possible for business leaders to increase productivity and reduce support costs.

“While some legacy data stores may be too costly or large to make a clean cutover,” says Wettemann, “looking at moving some or all CRM areas to modern apps that can integrate with old data sources will likely be worth the effort.”

A Partial Answer is Better than No Answer

It can be tempting to take channel-specific measurements like app downloads or click-through rates at face value. But without analytics or contextual information, the results can be deceptive. For example, “measuring who, and how many, download a company’s mobile application without being able to combine that with how they shop in physical locations (stores, bank branches, etc.) will give ‘false positives’ about digital’s importance in the overall growth strategy,” Wollan explains.

Looking Ahead

In addition to business leaders taking a more informed approach to their CRM strategies, vendors must do their part by providing more powerful and useful solutions. “Vendors will have to do a better job at not only providing table stakes capabilities of data management, data cleansing etc., but also embedded analytics to drive business outcomes,” says Leggett. Advanced analytics can add speed, scale, visualization, and predictive capabilities to business applications.

Wettemann agrees that “effectively managing unstructured data like content and using machine learning and other analytical tools to be more proactive in how to market, sell, and service customers is still emerging as an area with a lot of opportunity for benefit. The biggest, yet most basic, innovation is the productivity tools that deliver better, timelier, more complete CRM data without burdening sales and customer service people.”

Ultimately, CRM tools must become more “fluid” to enable businesses to keep pace with “non-stop customers,” Wollan observes. “The old customer journey of marketing-sales-service used to be linear, but has become much more fluid – a circular journey of discover-evaluate-purchase-use,” Wollan maintains. “This will mean breaking siloes of marketing-sales-service that most companies have used so successfully until now.”